Dr. Wolfgang Fuhl

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University of Tübingen
Dpt. of Computer Science
Human-Computer Interaction
Sand 14
72076 Tübingen
Germany

Telephone
+49 - (0) 70 71 - 29 - 70492
Telefax
+49 - (0) 70 71 - 29 - 50 62
E-Mail
wolfgang.fuhl@uni-tuebingen.de
Office
Sand 14, C206
Office hours
on appointment

Research Interest:

  • Computer Vision (Classical image processing, Rule based algorithms, Shape estimation, 3D pose estimation, Detection, Classification, Segmentation, 3D reconstruction, Image generation, Modern Image, Features (HOG, MSER, SIFT), Real time systems)
  • Machine Learning (Deep Neuronal Networks (Residual, Inception, Combinations, Recurrent), Tiny Convolutional Neuronal Networks, Real time Neuronal Networks (XOR, Binary, Tree), Unsupervised learning (Auto encoders, PCA), Support vector machines, Optimization, Decision Trees, KNN, GMM, transfer learning, Probabilistic (Naive Bays, HMM, CRF, Graph Models), Bagging, Boosting, Rule learning, PCA Networks, Scattering Networks, Clustering, Curve/Function fitting, evolutionary algorithms)
  • Eye Tracking (Real time feature extraction algorithms, Feature based gaze estimation, Appearance based gaze estimation, AOI generation, Scan path classification, Eye movement detection, Usability of eye tracking software, Data visualization)
  • Visualization (3D rendering, Data reduction, Interactive Visualizations, Splines)
  • Hardware (FPGAs, raspberry PI, Mobile Phones, NPU, GPU, CPU)

Assigned-Thesis-Topics:

  • Arduino Cloud for Mobile Phones, Benedikt Hosp (M.Sc.)
  • Implementation And Evaluation Of Methods For Object Recognition, Sebastian Lutz (M.Sc.)
  • EyeTrace - Saliency AOI Generation, Ying Meng (M.Sc.)
  • Vergleich von Aufmerksamkeitsmodellen auf der Basis dynamischer Fahrszenen, Erik Lemke (B.Sc.)
  • Extraktion der Blutgefäße des Auges aus Nahaufnahmen, Sotirios Pavlidis (B.Sc.)
  • Bewertung Maschinelle Lernalgorithmen für die Güte von Programmierkenntnissen, Christian Hackenbeck (B.Sc.)
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  • Bewertung und Umsetzung bewährter Echtzeitbildverarbeitungsmerkmale für den Einsatz in Webbrowsern, Amr Abdellatif (B.Sc.)
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  • Bewertung und Umsetzung echtzeitfähiger maschineller Lern Algorithmen für den Einsatz in Webbrowsern, Hao liu (B.Sc.)
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  • Erstellung und Bewertung eines Webbrowserbasierten Frameworks zur Datenakquise für Studien, Roufayda Salaheddine (B.Sc.)
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  • Erstellung und Bewertung einer Webplattformbasierten Datenhaltungs- und Bewertungssoftware für Studien, Oliwia Oles (B.Sc.)
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  • Improve Browser Watermarking with Eye Tracking, Nikolai Iraj Sanamrad (B.Sc.)
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  • Scan path Classification in dynamic scenes, Fadi Al-kayid (B.Sc. in progress)
  • Gaze based tessellation of objects in 3D scenes, Eric Goofers (M.Sc. in progress)

Publications

2021

Indicators of Training Success in Virtual Reality Using Head and Eye Movements

J. Gisler, J. Schneider, J. Handali, V. Holzwarth, C. Hirt, W. Fuhl, J. Brocke, and A. Kunz. IEEE International Symposium on Mixed and Augmented Reality POSTER (ISMAR), 2021.

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TEyeD: Over 20 Million Real-World Eye Images with Pupil, Eyelid, and Iris 2D and 3D Segmentations, 2D and 3D Landmarks, 3D Eyeball, Gaze Vector, and Eye Movement Types

Wolfgang Fuhl, Gjergji Kasneci, and Enkelejda Kasneci. IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2021.

PDF BIB Supplementary Material

Tensor Normalization and Full Distribution Training

Wolfgang Fuhl. arXiv preprint arXiv:2109.02345, 2021.

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1000 Pupil Segmentations in a Second using Haar Like Features and Statistical Learning

Wolfgang Fuhl, Johannes Schneider, and Enkelejda Kasneci. International Conference on Computer Vision Workshops, ICCVW, 2021.

PDF BIB Supplementary Material

A Multimodal Eye Movement Dataset and a Multimodal Eye Movement Segmentation Analysis

W. Fuhl and E Kasneci. Proceedings of the ACM Symposium on Eye Tracking Research & Applications (ETRA), 2021.

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The Gaze and Mouse Signal as additional Source for User Fingerprints in Browser Applications

W Fuhl, N Sanamrad, and E Kasneci. arXiv preprint arXiv:2101.03793. CoRR, 2021.

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Reinforcement learning for the privacy preservation and manipulation of eye tracking data

Wolfgang Fuhl, Efe Bozkir, and Enkelejda Kasneci. Proceedings of International Conference on Artificial Neural Networks, 2021.

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Differential Privacy for Eye Tracking with Temporal Correlations

Efe Bozkir, Onur Günlü, Wolfgang Fuhl, Rafael F. Schaefer, and Enkelejda Kasneci. PLoS ONE, 2021.

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Weight and Gradient Centralization in Deep Neural Networks

Wolfgang Fuhl and Enkelejda Kasneci. Proceedings of IEEE International Joint Conference on Neural Networks, 2021.

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Rotated Ring, Radial and Depth Wise Separable Radial Convolutions

Wolfgang Fuhl and Enkelejda Kasneci. Proceedings of the International Joint Conference on Neural Networks, 2021.

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Maximum and Leaky Maximum Propagation

Wolfgang Fuhl. arXiv preprint arXiv:2105.10277, 2021.

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55 Rides: Attention annotated Head and Gaze data during Naturalistic Driving

Thomas Kübler, Wolfgang Fuhl, Elena Wagner, and Enkelejda Kasneci. Eye-Tracking Research and Applications. ACM, 2021.

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2020

RemoteEye: An open-source high-speed remote eye tracker

Benedikt Hosp, Shahram Eivazi, Maximilian Maurer, Woflgang Fuhl, David Geisler, and Enkelejda Kasneci. Behavior Research Methods, pages 1–15. Springer, 2020.

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Training Decision Trees as Replacement for Convolution Layers

W. Fuhl, G. Kasneci, W. Rosenstiel, and E. Kasneci. Conference on Artificial Intelligence, AAAI, 2020.

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Tiny convolution, decision tree, and binary neuronal networks for robust and real time pupil outline estimation

W. Fuhl, H. Gao, and E. Kasneci. ACM Symposium on Eye Tracking Research & Applications, ETRA 2020. ACM, 2020.

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Neural networks for optical vector and eye ball parameter estimation

W. Fuhl, H. Gao, and E. Kasneci. ACM Symposium on Eye Tracking Research & Applications, ETRA 2020. ACM, 2020.

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A Novel Camera-Free Eye Tracking Sensor for Augmented Reality based on Laser Scanning

Johannes Meyer, Thomas Schlebusch, Wolfgang Fuhl, and Enkelejda Kasneci. Sensors Journal, pages 1-1. IEEE, 2020.

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Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction

Wolfgang Fuhl, Yao Rong, and Kasneci Enkelejda. Proceedings of the International Conference on Pattern Recognition, pages 0–0, 2020.

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Explainable Online Validation of Machine Learning Models for Practical Applications

Wolfgang Fuhl, Yao Rong, Thomas Motz, Michael Scheidt, Andreas Hartel, Andreas Koch, and Enkelejda Kasneci. Proceedings of the International Conference on Pattern Recognition, pages 0–0, 2020.

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Multi Layer Neural Networks as Replacement for Pooling Operations

Wolfgang Fuhl and Enkelejda Kasneci. arXiv preprint arXiv:2006.06969. CoRR, 2020.

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From perception to action using observed actions to learn gestures

Wolfgang Fuhl. User Modeling and User-Adapted Interaction, pages 1-18. Springer, 2020.

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2019

Encodji: Encoding Gaze Data Into Emoji Space for an Amusing Scanpath Classification Approach ;)

Wolfgang Fuhl, Efe Bozkir, Benedikt Hosp, Nora Castner, David Geisler, Thiago C., and Enkelejda Kasneci. Eye Tracking Research and Applications, 2019.

PDF BIB Supplementary Material

Ferns for area of interest free scanpath classification

W. Fuhl, N. Castner, T. C. Kübler, A. Lotz, W. Rosenstiel, and E. Kasneci. Proceedings of the 2019 ACM Symposium on Eye Tracking Research & Applications (ETRA) , 2019.

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Image-based extraction of eye features for robust eye tracking

W. Fuhl. PhD thesis. University of Tübingen, 2019.

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500,000 images closer to eyelid and pupil segmentation

W. Fuhl, W. Rosenstiel, and E. Kasneci. Computer Analysis of Images and Patterns, CAIP, 2019.

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The applicability of Cycle GANs for pupil and eyelid segmentation, data generation and image refinement

W. Fuhl, D. Geisler, W. Rosenstiel, and E. Kasneci. International Conference on Computer Vision Workshops, ICCVW, 2019.

PDF BIB Supplementary Material

Learning to validate the quality of detected landmarks

W. Fuhl and E. Kasneci. International Conference on Machine Vision, ICMV, 2019.

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2018

PuRe: Robust Pupil Detection for Real-Time Pervasive Eye Tracking

T. Santini, W. Fuhl, and E. Kasneci. Elsevier Computer Vision and Image Understanding To Appear, 2018.

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PuReST: Robust Pupil Tracking for Real-Time Pervasive Eye Tracking

T. Santini, W. Fuhl, and E. Kasneci. Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA), 2018.

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CBF:Circular binary features for robust and real-time pupil center detection

W. Fuhl, D. Geisler, T. Santini, T. Appel, W. Rosenstiel, and E. Kasneci. ACM Symposium on Eye Tracking Research & Applications, 2018.

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Automatic generation of saliency-based areas of interest

W. Fuhl, T. Kübler, T. Santini, and E. Kasneci. Symposium on Vision, Modeling and Visualization (VMV), 2018.

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Region of interest generation algorithms for eye tracking data

W. Fuhl, T. C. Kübler, H. Brinkmann, R. Rosenberg, W. Rosenstiel, and E. Kasneci. Third Workshop on Eye Tracking and Visualization (ETVIS), in conjunction with ACM ETRA, 2018.

PDF BIB Supplementary Material

MAM: Transfer learning for fully automatic video annotation and specialized detector creation

W. Fuhl, N. Castner, L. Zhuang, M. Holzer, W. Rosenstiel, and E. Kasneci. International Conference on Computer Vision Workshops, ICCVW, 2018.

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Eye movement velocity and gaze data generator for evaluation, robustness testing and assess of eye tracking software and visualization tools

W. Fuhl and E. Kasneci. Poster at Egocentric Perception, Interaction and Computing, EPIC, 2018.

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BORE: Boosted-oriented edge optimization for robust, real time remote pupil center detection

W. Fuhl, S. Eivazi, B. Hosp, A. Eivazi, W. Rosenstiel, and E. Kasneci. Eye Tracking Research and Applications, ETRA, 2018.

PDF BIB Supplementary Material

Rule based learning for eye movement type detection

W. Fuhl, N. Castner, and E. Kasneci. International Conference on Multimodal Interaction Workshops, ICMIW, 2018.

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Histogram of oriented velocities for eye movement detection

W. Fuhl, N. Castner, and E. Kasneci. International Conference on Multimodal Interaction Workshops, ICMIW, 2018.

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Eye movement simulation and detector creation to reduce laborious parameter adjustments

W. Fuhl, T. Santini, T. Kuebler, N. Castner, W. Rosenstiel, and E. Kasneci. arXiv preprint arXiv:1804.00970, 2018.

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2017

Saliency Sandbox: Bottom-Up Saliency Framework

D. Geisler, W. Fuhl, T. Santini, and E. Kasneci. 12th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), 2017.

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EyeRecToo: Open-Source Software for Real-Time Pervasive Head-Mounted Eye-Tracking

T. Santini, W. Fuhl, D. Geisler, and E. Kasneci. 12th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), 2017.

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EyeLad: Remote Eye Tracking Image Labeling Tool

W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, and E. Kasneci. 12th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), 2017.

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Fast and Robust Eyelid Outline and Aperture Detection in Real-World Scenarios

W. Fuhl, T. Santini, and E. Kasneci. IEEE Winter Conference on Applications of Computer Vision (WACV 2017), 2017.

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Ways of improving the precision of eye tracking data: Controlling the influence of dirt and dust on pupil detection

W. Fuhl, T. C. Kübler, D. Hospach, O. Bringmann, W. Rosenstiel, and E. Kasneci. Journal of Eye Movement Research 10(3), 2017.

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CalibMe: Fast and Unsupervised Eye Tracker Calibration for Gaze-Based Pervasive Human-Computer Interaction

T. Santini, W. Fuhl, and E. Kasneci. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017.

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Towards Intelligent Surgical Microscopes: Surgeons Gaze and Instrument Tracking

Shahram Eivazi, Wolfgang Fuhl, and Enkelejda Kasneci. Proceedings of the 22st International Conference on Intelligent User Interfaces, IUI 2017. ACM, 2017.

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Towards automatic skill evaluation in microsurgery

Shahram Eivazi, Michael Slupina, Wolfgang Fuhl, Hoorieh Afkari, Ahmad Hafez, and Enkelejda Kasneci. Proceedings of the 22st International Conference on Intelligent User Interfaces, IUI 2017. ACM, 2017.

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PupilNet v2.0: Convolutional Neural Networks for Robust Pupil Detection

W. Fuhl, T. Santini, G. Kasneci, and E. Kasneci. CoRR, 2017.

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Fast camera focus estimation for gaze-based focus control

W. Fuhl, T. Santini, and E. Kasneci. CoRR, 2017.

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Optimal eye movement strategies: a comparison of neurosurgeons gaze patterns when using a surgical microscope

S. Eivazi, A. Hafez, W. Fuhl, H. Afkari, E. Kasneci, M. Lehecka, and R. Bednarik. Acta Neurochirurgica, 2017.

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2016

EyeRec: An Open-source Data Acquisition Software for Head-mounted Eye-tracking

T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci. Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) 3: VISAPP: 386–391, 2016.

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ElSe: Ellipse Selection for Robust Pupil Detection in Real-World Environments

W. Fuhl, T. Santini, T. C. Kübler, and E. Kasneci. Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications (ETRA), pages 123–130, 2016.

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Bayesian Identification of Fixations, Saccades, and Smooth Pursuits

T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci. Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications (ETRA), pages 163–170, 2016.

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Pupil detection for head-mounted eye tracking in the wild: An evaluation of the state of the art

Wolfgang Fuhl, Marc Tonsen, Andreas Bulling, and Enkelejda Kasneci. Machine Vision and Applications, pages 1-14, 2016.

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Eyes Wide Open? Eyelid Location and Eye Aperture Estimation for Pervasive Eye Tracking in Real-World Scenarios

W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, W. Rosenstiel, and E. Kasneci. ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct publication – PETMEI 2016, 2016.

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Novel methods for analysis and visualization of saccade trajectories

T. C. Kübler, W. Fuhl, R. Rosenberg, W. Rosenstiel, and E. Kasneci. 3. ECCV Workshop VISART 2016, 2016.

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Non-Intrusive Practitioner Pupil Detection for Unmodified Microscope Oculars

W. Fuhl, T. Santini, C. Reichert, D. Claus, A. Herkommer, H. Bahmani, K. Rifai, S. Wahl, and E. Kasneci. Elsevier Computers in Biology and Medicine 79: 36-44, 2016.

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Evaluation of State-of-the-Art Pupil Detection Algorithms on Remote Eye Images

W. Fuhl, D. Geisler, T. Santini, and E. Kasneci. ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct publication – PETMEI 2016, 2016.

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Feature-based attentional influences on the accommodation response

H. Bahmani, W. Fuhl, E. Gutierrez, G. Kasneci, E. Kasneci, and S. Wahl. Vision Sciences Society Annual Meeting Abstract, 2016.

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PupilNet: Convolutional Neural Networks for Robust Pupil Detection

W. Fuhl, T. Santini, G. Kasneci, and E. Kasneci. CoRR, 2016.

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2015

Analysis of eye movements with Eyetrace

T. C. Kübler, K. Sippel, W. Fuhl, G. Schievelbein, J. Aufreiter, R. Rosenberg, W. Rosenstiel, and E. Kasneci. 574: 458-471. Biomedical Engineering Systems and Technologies. Communications in Computer and Information Science (CCIS). Springer International Publishing, 2015.

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Eyetrace2014: Eyetracking Data Analysis Tool

K. Sippel, T. C. Kübler, W. Fuhl, G. Schievelbein, R. Rosenberg, and W. Rosenstiel. 8th International Conference on Health Informatics, Healthinf 2015, 2015.

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Exploiting the potential of eye movements analysis in the driving context

E. Kasneci, T. C. Kübler, C. Braunagel, W. Fuhl, W. Stolzmann, and W. Rosenstiel. 15. Internationales Stuttgarter Symposium Automobil- und Motorentechnik. Springer Fachmedien Wiesbaden, 2015.

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ExCuSe: Robust Pupil Detection in Real-World Scenarios

W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci. 16th International Conference on Computer Analysis of Images and Patterns (CAIP 2015), 2015.

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Arbitrarily shaped areas of interest based on gaze density gradient

W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci. European Conference on Eye Movements, ECEM 2015, 2015.

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Teaching

Course Term
Programmierung in C/C++
Programmierung in C/C++
Seminar Advanced Topics in Human-Computer Interaction
Teamprojekt: Machine Learning in the Field of Eye Tracking
Teamprojekt: Machine Learning in the Field of Eye Tracking
Teamprojekt Machine Learning in the Field of Eye Tracking
Teamprojekt Remote Eye Tracking
User Experience
Advanced Topics in Perception Engineering
Advanced Topics in Perception Engineering
Programmieren mobiler eingebetteter Systeme
Programmieren mobiler eingebetteter Systeme
Programmieren mobiler eingebetteter Systeme
Programmieren mobiler eingebetteter Systeme
Technische Anwendungen der Informatik: Hard- und Software aktueller Eye-Tracking-Systeme
Technische Anwendungen der Informatik: Hard- und Software aktueller Eye-Tracking-Systeme
Seminar: Advanced Topics in Perception Engineering

Open Thesis Topics

Assigned Thesis Topics

Finished Thesis Topics

10.07.2019

Vein extraction and eye rotation determination

The first step is setting up an recording environment with fixed subject position. This environment is used for data acquisition with predefined head rotations of the subjects. Based on this data an algorithm has to be developed measuring the eyeball rotation of the subject. The resulting angle is then compared and validated based on the head rotation.

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10.07.2019

EyeTrace CUDA extesion

EyeTrace is a software for gaze data visualization and analysis. Due to the increasing amount of data these visualizations need more computation time. In this thesis existing visualizations should be implemented using CUDA for GPU computations. Additionally this includes a data storage model making it possible to shift the data between the GPU and the host computer. Due to the fact that nowadays not all computers have a CUDA capable card the modul should also allow CPU computations. This should be determined automatically by the module.

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10.07.2019

3D Eyeball generation based on vein motion

The first step is robust feature extraction. This can be done using SURF, SIFT, BRISK or MSER features if sufficient. Those features have to be mapped on features found in consecutive images. Based on the displacement a 3D model has to be computed. This model is used afterwards for gaze position estimation.

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